Many engineering problems are concerned with identifying a design that minimises or maximises certain parameters whilst satisfying certain constraints; in essence the aim of a design method is to find an optimum and feasible design.
Typically, potential designs are identified (commonly referred to as “solutions”) and their parameters evaluated against a cost function. Since, by definition, an optimal design is unknown prior to the optimisation process, known methods apply an equal amount of computing effort to all potential designs. Clearly most of these potential designs will be sub-optimal, which means that evaluating all potential solutions is a significant waste of processing resources.
Such computationally expensive design problems include identifying a shape and structure of aerodynamic bodies (aircraft wings, fuselage, motorbike fairings, racing car fairings) that need to withstand certain conditions. Typically well-known techniques such as Computational Fluid Dynamics (CFD) and Finite Element Analysis (FEA) are applied to identify an optimal design of such bodies, where, respectively, the flow over and force upon the body is modelled and the drag and yield point of the body identified. Although these techniques work well, they are extremely computationally expensive. In the area of CFD, convergence of solutions can take several hours, even for inviscid models (e.g. an Euler model (where fluid flowing over the body is assumed to have zero viscosity) run in respect of a single body configuration takes 3 hours on 4 parallel Pentium 4 processors). This means that it is impractical to run a full CFD analysis for many different body configurations.
In order to reduce the computational time associated with identifying an optimal object configuration, so-called Response Surface Models (RSM) have been developed. For the example of CFD, Response Surface Models are integrated with the more computationally expensive analysis methods by running a full CFD analysis in respect of several object configurations (typically between 10 and 100), and pooling the output of the respective CFD calculations in order to provide a landscape (a Response Surface) for searching for an optimum design. This method significantly decreases the amount of time required to identify optimum designs, but large amounts of computational time are nevertheless spent investigating object configurations that are sub-optimal.